Backend Engineer - Metrics Infrastructure

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We build infrastructure and tools that power metrics for autonomous vehicles and delivery robots. Our goal is to shorten the feedback loop: make it straightforward to develop, run, and use metrics ric calculations are often complex compute graphs (multiple languages) with heavy compute; across millions of miles and simulations, they produce terabytes of results. A key part of the job is choosing storage layouts and schemas that keep inserts efficient and reads fast.

You will design, develop, and operate the platform for metrics: data models and storage, scalable pipelines, and a developer‑friendly framework for writing, testing, and shipping metrics. The role includes close collaboration with metric authors and with metric users—development, analytics, and QA—and ensuring reliable end‑to‑end delivery of metric results.

• Own the metrics platform: clear schemas, storage/layouts for efficient inserts and fast reads, simple versioning.
• Build and maintain the framework for writing/running metrics (interfaces, examples, local run, CI/compat checks).
• Create a test system for metrics and pipelines (unit / contract / regression on synthetic and sampled data).
• Operate the compute and storage paths in production; monitor, debug, and keep the system stable and cost‑aware.
• Partner with metric authors and with development/analytics/QA to plan changes and land them safely.

• Strong SQL (JOINs, window functions, CTEs); ability to read plans and speed up slow queries.
• Data structures & algorithms—know when O(nlogn) matters and choose the right structures.
• Experience with databases:
  Postgre
  
  SQL, Click House; understanding OLAP vs. OLTP trade‑offs.
• Workflow orchestration experience (Airflow / Argo / Prefect / Dagster—any is fine).
• Data libs & validation:
  Num Py, pandas, Pydantic (or equivalents).
• Experience building web services (Django / FastAPI / Flask—stack flexible).

• C++ exposure (reading, small changes, or components in the compute graph).
• Infrastructure for ML‑adjacent metrics/evaluation.
• Parquet & object‑storage layout/partitioning;
  Kafka/task queues; basic observability (logs/metrics/traces).

• Mid‑Senior level

• Full-time

• Technology, Information and Internet

• Medical insurance
• Vision insurance
• 401(k)
• Paid maternity leave

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Austin, TX $90,000.00-$ 2 months ago

Austin, Texas Metropolitan Area 2 days ago